Aimed at revolutionizing our understanding of the brain, the BRAIN initiative calls for ?improvement of existing non-invasive neuromodulation? techniques. There is presently great interest in transcranial Direct Current Stimulation (tDCS), which is deployable, well tolerated, and carries the promise of targeted neuromodulation. Computational models of tDCS predict individual brain current flow for a given electrode configuration (?montage?), and predict that optimized targeting montages can achieve more focal cortical stimulation. Through three innovations, this proposal removes existing barriers limiting access to computational models that will allow researchers to individually tailor electrode montages for desired cortical targets so as to optimize clinical outcomes and address specific research hypotheses. First, a decade of technical innovation in automated image segmentation and high- throughput current flow modeling will be enhanced and encoded in cloud-enabled open-source. Second, state-of-the-art MRI mapping of tDCS current distribution will validate and refine model methods. Third, stand-alone and web-based modeling client software will be deployed with computationally demanding steps implemented on servers. Only as a result of algorithmic optimization can the modeling process be divided into two steps: a cloud-based computationally intensive processing on servers, and then simulations taking just seconds by researchers using client software on conventional PC. These innovations result in a process that previously required extensive expertise and labor, super-computers and numerous iterations instead being reduced to a single step, requiring seconds on a conventional PC. In addition, we will supply the MRI protocol for in vivo mapping of tDCS current flow. In an exploratory aim, MRI mapping will test modeling predictions on deep structure targeting with tDCS. Directly responsive to the RFA, the outcome of this proposal is a toolbox for the optimization of tDCS spatial precision to enhance the rigor of tDCS research aimed at understanding the brain and for treating disease. Our approach is unique in integrating the scalability, rigor, and transparency of opens-source (server side) with highly assessable GUI control software (client side), while being exceptionally robust (e.g. non-ideal scan quality) and flexible (e.g. conventional pad or High-Definition electrodes).